@Technion_RL

Official account covering research performed in the various #ReinforcementLearning labs at the @TechnionLive

 Haifa, Israel
rlrl.net.technion.ac.il
Joined October 2019
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Deep networks combined with finite memory poses a problem for bandit-based algorithms. In this blog post, Ofir explains their method for overcoming the drift in the learned features and avoiding catastrophic forgetting! rlrl.net.technion.ac.il/2021…
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Interested in learning how to detect reward deterioration? Check out the blog post by Ido Greenberg! rlrl.net.technion.ac.il/2021…
Check out @carmelrabinovi1 's new work! Constrastive domain randomization for sim-to-real transfer!
Carmel Rabinovitz@CarmelRabinovi17 Jun 2021
Excited to share our new #ICRA2021 paper on “Contrastive Domain Randomization” (CDR) with my amazing collaborators @nikogrupen, and @AvivTamar1: Website: sites.google.com/view/contra… Paper: arxiv.org/abs/2103.11144 Code: github.com/carmelrabinov/cdr #robotics #ContrastiveLearning #AI
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It's been a while without updates. Let's cover some of the recent publications from the various RL groups at the @TechnionLive ! Thread.
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Bandits with Partially Observable Confounded Data - UAI @guytenn, @ShalitUri, @MannorShie and Yonathan Efroni
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Action Redundancy in Reinforcement Learning - UAI Nir Baram, @guytenn and @MannorShie
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Awesome blog post by Orr, Omer and Raveh! Interested in RL and robotics? Certainly worth checking this out!
Orr Krupnik@orrkrup21 Apr 2021
What happens when you set out to reproduce a "reproducible robotics benchmark"? Omer and Raveh tried it out with #REPLAB! Their findings are detailed in the new blog post at @Technion_RL. TL;DR: it takes some work, but it's definitely possible!
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Super excited for the first Israeli RL day! 🙌
Orr Krupnik@orrkrup29 Mar 2021
The first Israeli RL Day will take place on Apr. 7th! Program is packed with great speakers, plus keynotes by @AvivTamar1, @MannorShie and Yishay Mansour. Schedule details at israel-rl-day.github.io. #IRLD2021
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Interested in #RealWorld applications of #ReinforcementLearning? Check out our recent work, “Inverse Reinforcement Learning in Contextual MDPs” where we learn from clinicians how to treat patients with Sepsis! Paper: bit.ly/381H6Da Code: github.com/coirl/coirl_code

Inverse Reinforcement Learning in Contextual MDPs

We consider the task of Inverse Reinforcement Learning in Contextual Markov Decision Processes (MDPs). In this setting, contexts, which define the reward and transition kernel, are sampled from a...

arxiv.org
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To evaluate our algorithm we use the MIMIC-III data set mimic.physionet.org/ @MIT_IMES. We focus on Sepsis treatment, which recently emerged as a benchmark for RL algorithms, and achieve new SOTA results.
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Work by @BeloStav, linkedin.com/in/philip-korsu…, @TZahavy, @tesslerc, @MannorShie To be featured in a special issue on RL for Real Life @Springer @MLJ_Social, by (@yuxili99, @AlborzGr, @LihongLi20, @CsabaSzepesvari, Tao Wang). link.medium.com/9dkamunnCcb

Philip Korsunsky - United States | Professional Profile | LinkedIn

Experience: TwelveLabs · Location: United States · 333 connections on LinkedIn. View Philip Korsunsky’s profile on LinkedIn, a professional community of 1 billion members.

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